17 results about "Hepatic veins" patented technology

The present application relates to the technical field of medicine, and discloses application of gastrodin in preparation of medicine for preventing and treating radioactive liver injury, wherein the radioactive liver injury is liver injury caused by ionizing radiation exposure. It is found that the gastrodin can effectively intervene in specific mechanism of the radioactive liver injury, significantly reduce the mortality of the radioactive liver injury mice, reverse the hepatic veno-occlusive disease and the core pathological features of liver fibrosis of the radioactive liver injury, and more specifically treat the radioactive liver injury. On the other hand, the gastrodin can be used before radiation exposure to prevent serious radioactive liver injury after radiation exposure.

A system, apparatus, and method of using the same are disclosed for carrying out a transvascular procedure such as a Transjugular Intrahepatic Portosystemic Shunt (TIPS) procedure using energy to create a tract between the hepatic vein and the portal vein. The present invention provides a method using a flexible radiofrequency (RF) catheter having a lumen therethrough. The method involves the steps of advancing the flexible RF catheter into a first vessel; advancing a guiding sheath overtop of the flexible RF catheter; steering the guiding sheath to direct a distal tip of the RF catheter towards a second vessel; and, delivering RF energy via the flexible RF catheter, forming a tract from the first vessel and entering the second vessel.

The application discloses a blood vessel identification system, device and storage medium. The system comprises a processor configured to execute the following blood vessel identification method, which comprises: inputting a blood vessel segmentation template into a trained first image processing model to obtain a global feature map; determining a structure point set corresponding to the blood vessel in the blood vessel segmentation template, determining an adjacency matrix of each structure point in the structure point set in the blood vessel segmentation template and feature data of each structure point in the global feature map, and the structure point set comprising position coordinates of at least two structure points used for representing a blood vessel direction; inputting the structure point set, the adjacency matrix and the feature data corresponding to each structure point in the structure point set into a trained second image processing model to obtain an identification result; and determining a target class identification of each blood vessel in the blood vessel segmentation template according to the identification result and the blood vessel segmentation template. The application solves the problem that the existing liver vein and portal vein distinguishing method is low in robustness.

The invention relates to the technical field of medicines, and discloses application of gastrodin in preparation of a medicine for preventing and treating radioactive liver injury, and the radioactive liver injury is liver injury caused by ionizing radiation exposure. The gastrodin is found to be capable of effectively intervening a specific mechanism of the radiation-induced liver injury, so that the death rate of mice with the radiation-induced liver injury is remarkably reduced, meanwhile, the core pathological characteristics of hepatic vein occlusion and hepatic fibrosis of the radiation-induced liver injury are reversed, and the radiation-induced liver injury is treated in a more targeted manner. On the other hand, gastrodin is used before radiation exposure, so that serious radioactive liver injury after radiation exposure can be prevented.

The application discloses a liver intersegmental vein three-dimensional image artificial intelligence identification method and related equipment, and belongs to the medical image processing field. The method comprises the following steps: acquiring abdominal medical image data of a target patient; establishing an original liver segment model and an extended liver segment model of the target patient based on the image data, and extracting an intersegmental liver vein image in an intersection region of the original liver segment model and the extended liver segment model; the original liver segment model is obtained by reconstruction based on the abdominal medical image data of the target patient, and the extended liver segment model is obtained by extension operation based on the original liver segment model; inputting the extracted intersegmental liver vein image into a pre-trained binary classification model to obtain a liver intersegmental vein three-dimensional image artificial intelligence identification result. The application converts the recognition and identification of the intersegmental liver vein into an automatic extraction and intelligent identification process, and provides accurate and repeatable preoperative evaluation basis for liver surgery planning.

The invention relates to the technical field of data processing, in particular to a portal vein hypertension monitoring method based on multi-modal liver blood vessel parameters, which comprises the following steps: acquiring a CT image, an MRI image, an ultrasonic image and a liver pathological section of a patient, and constructing a multi-modal data source; extracting anatomical structure parameters, functional characteristic parameters and pathophysiologic phenotype parameters of liver blood vessels from the constructed multi-modal data source, and constructing a multi-modal representation library; and inputting the parameters in the multi-modal representation library into a constructed hybrid expert model comprising an expert network, a gating network and an integrated mechanism to obtain a predicted value of the hepatic vein pressure gradient HVPG. Therefore, accurate extraction of blood vessel parameters under a multi-mode image is used, the anti-noise capability is improved, and the limitation of a single mode is overcome; and non-invasive detection is performed on the hepatic vein pressure by using a hybrid expert model, so that the problem of HVPG invasive detection is solved.

The invention provides an automatic liver segmentation modeling method and system based on a hybrid neural network, and relates to the technical field of medical imagines.The method comprises the steps that a collected original liver image is preprocessed, and a three-dimensional liver image is obtained; wherein the three-dimensional liver image comprises liver parenchyma, portal vein and liver vein; inputting the three-dimensional liver image into a trained segmentation model to obtain a liver parenchyma mask, a portal vein mask and a liver vein mask; based on the liver parenchyma mask, the portal vein mask and the liver vein mask, dividing the liver parenchyma into a plurality of drainage basin partitions; determining a standard liver segment corresponding to each drainage basin partition based on a preset liver segment division rule; and based on the standard liver segment corresponding to the drainage basin subarea, performing elastic deformation on the drainage basin subarea to obtain a deformed drainage basin subarea. According to the invention, individual vascular variation characteristics of patients can be reflected.

The invention relates to the technical field of fluid mechanics, and provides a liver sinus blood flow numerical simulation method and device, electronic equipment and a computer program product. The method comprises the following steps: acquiring a three-dimensional geometric model of a liver blood sinus area of a patient; setting blood flow in the portal vein and the hepatic vein as incompressible Newtonian fluid, and constructing a three-dimensional transient Darcy law equation for representing hepatic sinus blood flow parameters in the three-dimensional geometric model; and solving the three-dimensional transient Darcy law equation to obtain a blood flow numerical simulation result of the liver blood sinus area. According to the method, a three-dimensional transient Darcy law equation is adopted as a mathematical model of hepatic sinus blood flow, on the basis of the characteristics of the three-dimensional transient Darcy law equation, the seepage flow characteristics of blood in a hepatic sinus porous medium structure can be well described, and the blood flow distribution rule in hepatic sinus is accurately reflected; therefore, an accurate liver sinus blood flow numerical simulation result is obtained.

The present invention relates to a transient intentional ischemia of a part of the liver by occlusion of a selected hepatic vein, subsequently causing reperfusion injury, useful for the treatment of cancer via the endogenous release of liver enzymes, including liver arginase.

The application provides a kind of liver CT image blood vessel segmentation mask fracture repair and topological analysis method, specific steps include: 1) skeletonization is carried out to liver blood vessel segmentation mask, and the blood vessel skeleton, skeleton end point and blood vessel radius rough value at skeleton point are extracted;2) without considering the removal of hepatic vein and portal vein error adhesion, for the purpose of fracture repair, obtain connected blood vessel center line ①;3) considering the removal of hepatic vein and portal vein possible error adhesion, set more strict connection condition, obtain the broken blood vessel center line, then for the purpose of classification, obtain the blood vessel center line ② containing fracture and obvious distinction of hepatic vein and portal vein;4) merge the above center line ① and ②, reconstruct the missing blood vessel segment in the original blood vessel segmentation mask, merge into the original segmentation mask, obtain the final fracture repair blood vessel mask and center line topological structure.

The invention discloses an operation plan planning method based on an AI algorithm. The operation plan planning method comprises the step of scanning organs, portal veins, hepatic arteries, hepatic veins and tumors of a patient before an operation. The operation date of a patient is determined according to the disease condition of the patient, a doctor in a first operation group possibly performs other operations at the operation date of the patient, in order to avoid the situation, the invention further provides a second operation group, and the doctor which cannot perform the operation on the day is removed from the first operation group. Due to the fact that different patients have different surgical difficulties, the number of doctors in the surgical group needing to be predicted is different, if the number of doctors in the second surgical group cannot meet the surgical requirement after removal, the invention further provides a third surgical group, and based on the first surgical group, the second surgical group and the third surgical group, the system can well meet the surgical requirement of any difficulty, and the surgical efficiency is improved. And a team consisting of top doctors is used for operating patients, so that flexible deployment is realized, and the requirements of hospitals are met.

An organ blood flow monitor includes an ultrasound transducer probe and an adhesive patch connected to the ultrasound transducer probe for attaching the ultrasound transducer probe to a patient. The organ blood flow monitor also includes a system memory storing monitoring software code with an organ recognition module. A processor of the organ blood flow monitor is configured to execute the organ recognition module to scan a Doppler flow signal sensed in an abdomen of the patient by the ultrasound transducer probe for at least two cardiac cycles of the patient. The processor also executes the organ recognition module to process the scanned Doppler flow signal through a renal heuristic algorithm, a portal vein heuristic algorithm, and / or a hepatic vein heuristic algorithm of the organ recognition module to identify whether the scanned Doppler flow signal represents renal blood flow, portal vein flow, or hepatic vein flow of the patient.

The devices and methods generally relate to vibratable sensors for measuring ambient fluid pressure, in particular implantable sensors. The devices and methods are suited to implantation within the body to monitor physiological conditions, such as portal and / or hepatic venous blood pressure, and allow frequent, remote interrogation of venous pressure. The sensor devices are relatively small compared to conventional devices for measuring fluid pressure and can be implanted in the portohepatic venous system, whereas conventional devices are too large. The small size of the device is accomplished by using a thick sensor membrane, compared to conventional devices, and by limiting the size of additional elements of the device relative to the size of the sensor membrane. The thicker sensor member also obviates the need for multiple sensor arrays and maintains the accuracy and robustness of the sensor device. A data capture, processing, and display system provides a pressure measurement reading.

The present invention relates to a hypotonic fluid, e.g., water for injection, useful for the treatment of cancer via the endogenous release of liver enzymes, including liver arginase, by infusion of the said fluid into the hepatic vein of a liver segment.

This application provides an automated liver segmentation modeling method and system based on a hybrid neural network, relating to the field of medical imaging technology. The method includes: preprocessing acquired raw liver images to obtain a three-dimensional liver image; wherein the three-dimensional liver image includes liver parenchyma, portal vein, and hepatic vein; inputting the three-dimensional liver image into a trained segmentation model to obtain liver parenchyma masks, portal vein masks, and hepatic vein masks; dividing the liver parenchyma into multiple watershed partitions based on the liver parenchyma masks, portal vein masks, and hepatic vein masks; determining the standard liver segment corresponding to each watershed partition based on preset liver segmentation rules; and elastically deforming the watershed partitions based on the standard liver segments corresponding to the watershed partitions to obtain deformed watershed partitions. This application can reflect the individualized vascular variation characteristics of patients.

The application discloses a kind of hepatic venous pressure gradient measurement method, measurement system, electronic equipment and medium, the measurement method includes: the blood vessel model of liver is constructed;By the way of fluid mechanics, the blood flow of hepatic vein under normal circumstances and the blood flow of hepatic vein under the condition of obstruction are simulated in blood vessel model based on the same preset boundary condition, to calculate the hepatic vein free pressure and hepatic vein wedge pressure at the first preset position of hepatic vein respectively;According to hepatic vein free pressure and hepatic vein wedge pressure obtains hepatic venous pressure gradient.The application can use the calculation of CFD, in the case of non-invasive, based on the liver image of the user to be detected shot, accurately and quickly get accurate virtual hepatic venous pressure gradient, can replace the invasive measurement of hepatic venous pressure gradient, provides accurate data for clinical portal hypertension etc..